US5895447A
Expired / Lapsed
US
⏱️ 0.0 years remaining
Speech recognition using thresholded speaker class model selection or model adaptation
Assignee: International Business Machines Corp
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Filing: 1997-01-28
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Granted: 1999-04-20
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Expires: 2017-01-28
Abstract
Abstract Clusters of quantized feature vectors are processed against each other using a threshold distance value to cluster mean values of sets of parameters contained in speaker specific codebooks to form classes of speakers against which feature vectors computed from an arbitrary input speech signal can be compared to identify a speaker class. The number of codebooks considered in the comparison may be thus reduced to limit mixture elements which engender ambiguity and reduce system response speed when the speaker population becomes large. A speaker class processing model which is speaker independent within the class may be trained on one or more members of the class and selected for implementation in a speech recognition processor in accordance with the speaker class recognized to further improve speech recognition to level comparable to that of a speaker dependent model. Formation of speaker classes can be supervised by identification of groups of speakers to be included in the class and the speaker class dependent model trained on members of a respective group.
Inventors
- 👤 Abraham Poovakunnel Ittycheriah
- 👤 Stephane Herman Maes
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-01 13:13
CPC Classifications
G; G10; G10L; G10L15/00; G10L15/06; G10L15/065; G10L15/07; G10L21/00; G10L21/02; G10L21/0272; G10L25/00; G10L25/03; G10L25/12
Claims Analysis
Total Claims: 20
Claim 1
Independent Claim
91 words
A speech processing system including means for clustering information values representing respective frames of utterances of a plurality of speakers by speaker class in accordance with a threshold value to provide speaker class specific clusters of information, means for comparing information representing frames of an utterance of a speaker with respective clusters of said speaker class specific clusters of information to identify a speaker class, and means for processing speech information with a speaker class dependent model selected in accordance with a speaker class identified by said means for comparing information.
Claim 2
Dependent Claim
91 words
A speech processing system including means for clustering information values representing respective frames of utterances of a plurality of speakers by speaker class in accordance with a threshold value to provide speaker class specific clusters of information, means for comparing information representing frames of an utterance of a speaker with respective clusters of said speaker class specific clusters of information to identify a speaker class, and means for processing speech information with a speaker class dependent model selected in accordance with a speaker class identified by said means for comparing information.
Claim 3
Dependent Claim
33 words
A system as recited in claim 1, further including means for supervising a class with which a speaker may be associated, wherein said means for clustering is responsive to said means for supervising.
Claim 4
Dependent Claim
33 words
A system as recited in claim 2, further including means for training said speaker class dependent model in accordance with codebooks corresponding to speakers in a class identified by said means for supervising.
Claim 5
Dependent Claim
24 words
A system as recited in claim 3, wherein said codebooks of a speaker class are adapted in response to a speaker class dependent model.
Claim 6
Dependent Claim
83 words
A system as recited in claim 1, wherein said means for comparing includes means for sampling frames of said input speech signal, means for computing a feature vectors from frames of said input speech signal, means for comparing parameters of ones of said feature vectors computed in said computing step with said stored mean and variance values to derive a score, and means for counting the number of feature vectors which correspond to each said codebook responsive to said means for comparing parameters.
Claim 7
Dependent Claim
18 words
A system as recited in claim 1, wherein said means for comparing information includes means for pattern recognition.
Claim 8
Dependent Claim
36 words
A system as recited in claim 1, further including means for processing said speech information in accordance with a speaker independent model prior to completion of identification of a class by said means for comparing information.
Claim 9
Dependent Claim
36 words
A system as recited in claim 7, further including means for processing said speech information in accordance with a speaker dependent model subsequent to completion of identification of a class by said means for comparing information.
Claim 10
Independent Claim
84 words
A method of operating a speech recognition system, said method comprising the steps of identifying a speaker class by comparing an input speech signal with a stored representation of speech signals corresponding to a speaker class, in accordance with a threshold value, providing a speaker class dependent speech processing model to said speech recognition system in accordance with results of said identifying step, said speech processing model being speaker independent within a speaker class, and processing said speech signal with said speech processing model.
Claim 11
Independent Claim
84 words
A method of operating a speech recognition system, said method comprising the steps of identifying a speaker class by comparing an input speech signal with a stored representation of speech signals corresponding to a speaker class, in accordance with a threshold value, providing a speaker class dependent speech processing model to said speech recognition system in accordance with results of said identifying step, said speech processing model being speaker independent within a speaker class, and processing said speech signal with said speech processing model.
Claim 12
Dependent Claim
123 words
A method as recited in claim 9, wherein said stored representation of speech signals includes a plurality of codebooks, each codebook including a plurality of codewords comprising mean and variance values of parameters of clusters of feature vectors computed from frames of speech signals corresponding to an enrolled speaker and wherein said identifying step includes the steps of sampling frames of said input speech signal, computing a feature vectors from frames of said input speech signal, comparing parameters of ones of said feature vectors computed in said computing step with said stored mean and variance values to derive a score, and counting the number of feature vectors which correspond to each said codebook in accordance with results of said step of comparing parameters.
Claim 13
Dependent Claim
16 words
A method as recited in claim 9, wherein said identifying step includes a template matching process.
Claim 14
Dependent Claim
30 words
A method as recited in claim 9, including the further step of processing said speech signal in accordance with a speaker independent model prior to completion of said identifying step.
Claim 15
Dependent Claim
30 words
A method as recited in claim 9, including the further step of processing said speech signal in accordance with a speaker dependent model subsequent to completion of said identifying step.
Claim 16
Dependent Claim
40 words
A method as recited in claim 9, including the further step of processing said speech signal in accordance with a speaker independent model subsequent to completion of said identifying step when said identifying step does not identify an enrolled speaker.
Claim 17
Dependent Claim
28 words
A method as recited in claim 9, including the further step of forming said stored representation of speech signals corresponding to a speaker class by clustering of codewords.
Claim 18
Dependent Claim
32 words
A method as recited in claim 15, including the further step of supervising formation of said stored representation by identifying codewords which can be clustered by identification of a group of speakers.
Claim 19
Dependent Claim
22 words
A method as recited in claim 16, including the further step of a consistency check to accept or reject the identified class.
Claim 20
Dependent Claim
31 words
A method as recited in claim 16, including the further step of adapting said stored representation of speech signals corresponding to a class using said speaker class dependent speech processing model.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2002-04-19 | 2002-10-19 | 2003-04-20 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2006-04-19 | 2006-10-19 | 2007-04-20 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2010-04-19 | 2010-10-19 | 2011-04-20 | $7700.00 | Window Closed / Lapsed |